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Discussion papers
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Peer-reviewed comment 04 Jan 2019

Peer-reviewed comment | 04 Jan 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Earth System Science Data (ESSD).

Statistical downscaling of water vapour satellite measurements from profiles of tropical ice clouds

Giulia Carella1,2, Mathieu Vrac1, Hélène Brogniez2, Pascal Yiou1, and Hélène Chepfer3 Giulia Carella et al.
  • 1Laboratoire des Sciences du Climat et de l'Environnement (LSCE/IPSL, CNRS - CEA - UVSQ - Université Paris-Saclay), Orme des Merisiers, Gif-sur-Yvette, France
  • 2Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS), Guyancourt, France
  • 3Laboratoire de Météorologie Dynamique (LMD/IPSL, Sorbonne Université, Ecole Polytechnique, CNRS), Paris, France

Abstract. Multi-scale interactions between the main players of the atmospheric water cycle are poorly understood, even in present-day climate and represent one of the main sources of uncertainty among future climate projections. Here, we present a method to downscale observations of relative humidity available from the passive microwave sounder SAPHIR at a nominal horizontal resolution of 10 km to the finer resolution of 90 m using scattering ratio profiles from the lidar CALIPSO. With the scattering ratio profiles as covariates, an iterative approach applied to a non-parametric regression model based on Quantile Random Forest is used to effectively incorporate into the predicted relative humidity structure the high-resolution variability from cloud profiles. Results are presented for tropical ice clouds over the ocean: based on the coefficient of determination (with respect to the observed relative humidity) and the Continuous Rank Probability Skill Score (with respect to the climatology), we conclude that we are able to successfully predict, at the resolution of cloud measurements, the relative humidity along the whole troposphere, yet ensuring the best possible coherence with the values observed by SAPHIR. By providing a method to generate pseudo-observations of relative humidity (at high spatial resolution) from simultaneous co-located cloud profiles, this work will help revisiting some of the current key barriers in atmospheric science.

Giulia Carella et al.
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Giulia Carella et al.
Data sets

Downscaled Relative Humidity profiles for tropical ice clouds G. Carella, M. Vrac, H. Brogniez, P. Yiou, and H. Chepfer

Giulia Carella et al.
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Short summary
Observations of relative humidity for ice clouds over the tropical oceans from a passive microwave sounder are downscaled by incorporating the high-resolution variability derived from simultaneous co-located cloud profiles from a lidar. By improving the understanding at the resolution of cloud measurements of water vapour – clouds interactions, this method will help revisiting some of the current key barriers to reduce the uncertainty in climate model projections.
Observations of relative humidity for ice clouds over the tropical oceans from a passive...